On Effective Personalized Music Retrieval By Exploring Online User Behaviors,
2016
Singapore Management University
On Effective Personalized Music Retrieval By Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of personalized text based music retrieval which takes users’ music preferences on songs into account via the analysis of online listening behaviours and social tags. Towards the goal, a novel DualLayer Music Preference Topic Model (DL-MPTM) is proposed to construct latent music interest space and characterize the correlations among (user, song, term). Based on the DL-MPTM, we further develop an effective personalized music retrieval system. To evaluate the system’s performance, extensive experimental studies have been conducted over two test collections to compare the proposed method with the state-of-the-art music retrieval methods. The results …
Ordinal Text Quantification,
2016
Singapore Management University
Ordinal Text Quantification, Giovanni Da San Martino, Wei Gao, Fabrizio Sebastiani
Research Collection School Of Computing and Information Systems
In recent years there has been a growing interest in text quantification, a supervised learning task where the goal is to accurately estimate, in an unlabelled set of items, the prevalence (or "relative frequency") of each class c in a predefined set C. Text quantification has several applications, and is a dominant concern in fields such as market research, the social sciences, political science, and epidemiology. In this paper we tackle, for the first time, the problem of ordinal text quantification, defined as the task of performing text quantification when a total order is defined on the set of classes; …
Robust Median Reversion Strategy For Online Portfolio Selection,
2016
East China University of Science and Technology
Robust Median Reversion Strategy For Online Portfolio Selection, Dingjiang Huang, Junlong Zhou, Bin Li, Hoi, Steven C. H., Shuigeng Zhou
Research Collection School Of Computing and Information Systems
On-line portfolio selection has been attracting increasing interests from artificial intelligence community in recent decades. Mean reversion, as one most frequent pattern in financial markets, plays an important role in some state-of-the-art strategies. Though successful in certain datasets, existing mean reversion strategies do not fully consider noises and outliers in the data, leading to estimation error and thus non-optimal portfolios, which results in poor performance in practice. To overcome the limitation, we propose to exploit the reversion phenomenon by robust L1-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal portfolios based …
Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents,
2016
Singapore Management University
Word Clouds With Latent Variable Analysis For Visual Comparison Of Documents, Tuan M. V. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Word cloud is a visualization form for text that is recognized for its aesthetic, social, and analytical values. Here, we are concerned with deepening its analytical value for visual comparison of documents. To aid comparative analysis of two or more documents, users need to be able to perceive similarities and differences among documents through their word clouds. However, as we are dealing with text, approaches that treat words independently may impede accurate discernment of similarities among word clouds containing different words of related meanings. We therefore motivate the principle of displaying related words in a coherent manner, and propose to …
Detecting Rumors From Microblogs With Recurrent Neural Networks,
2016
Singapore Management University
Detecting Rumors From Microblogs With Recurrent Neural Networks, Jing Ma, Wei Gao, Prasenjit Mitra, Sejeong Kwon, Bernard J. Jansen, Kam-Fai Wong, Meeyoung Cha
Research Collection School Of Computing and Information Systems
Microblogging platforms are an ideal place for spreading rumors and automatically debunking rumors is a crucial problem. To detect rumors, existing approaches have relied on hand-crafted features for employing machine learning algorithms that require daunting manual effort. Upon facing a dubious claim, people dispute its truthfulness by posting various cues over time, which generates long-distance dependencies of evidence. This paper presents a novel method that learns continuous representations of microblog events for identifying rumors. The proposed model is based on recurrent neural networks (RNN) for learning the hidden representations that capture the variation of contextual information of relevant posts over …
Three Strategies To Success: Learning Adversary Models In Security Games,
2016
Singapore Management University
Three Strategies To Success: Learning Adversary Models In Security Games, Nika Haghtalab, Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Ariel D. Procaccia, Milind Tambe
Research Collection School Of Computing and Information Systems
State-of-the-art applications of Stackelberg security games -- including wildlife protection -- offer a wealth of data, which can be used to learn the behavior of the adversary. But existing approaches either make strong assumptions about the structure of the data, or gather new data through online algorithms that are likely to play severely suboptimal strategies. We develop a new approach to learning the parameters of the behavioral model of a bounded rational attacker (thereby pinpointing a near optimal strategy), by observing how the attacker responds to only three defender strategies. We also validate our approach using experiments on real and …
On Effective Personalized Music Retrieval Via Exploring Online User Behaviors,
2016
Singapore Management University
On Effective Personalized Music Retrieval Via Exploring Online User Behaviors, Zhiyong Cheng, Jialie Shen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In this paper, we study the problem of personalized text based music retrieval which takes users' music preferences on songs into account via the analysis of online listening behaviours and social tags. Towards the goal, a novel Dual-Layer Music Preference Topic Model (DL-MPTM) is proposed to construct latent music interest space and characterize the correlations among (user, song, term). Based on the DL-MPTM, we further develop an effective personalized music retrieval system. To evaluate the system's performance, extensive experimental studies have been conducted over two test collections to compare the proposed method with the state-of-the-art music retrieval methods. The results …
Where Is The Goldmine? Finding Promising Business Locations Through Facebook Data Analytics,
2016
Singapore Management University
Where Is The Goldmine? Finding Promising Business Locations Through Facebook Data Analytics, Jovian Lin, Richard Oentaryo, Ee-Peng Lim, Casey Vu, Adrian Vu, Agus Kwee
Research Collection School Of Computing and Information Systems
If you were to open your own cafe, would you not want to effortlessly identify the most suitable location to set up your shop? Choosing an optimal physical location is a critical decision for numerous businesses, as many factors contribute to the final choice of the location. In this paper, we seek to address the issue by investigating the use of publicly available Facebook Pages data-which include user "check-ins", types of business, and business locations-to evaluate a user-selected physical location with respect to a type of business. Using a dataset of 20,877 food businesses in Singapore, we conduct analysis of …
Learning Compact Visual Representation With Canonical Views For Robust Mobile Landmark Search,
2016
Singapore Management University
Learning Compact Visual Representation With Canonical Views For Robust Mobile Landmark Search, Lei Zhu, Jialie Shen, Xiaobai Liu, Liang Xie, Liqiang Nie
Research Collection School Of Computing and Information Systems
Mobile Landmark Search (MLS) recently receives increasing attention. However, it still remains unsolved due to two important issues. One is high bandwidth consumption of query transmission, and the other is the huge visual variations of query images. This paper proposes a Canonical View based Compact Visual Representation (2CVR) to handle these problems via novel three-stage learning. First, a submodular function is designed to measure visual representativeness and redundancy of a view set. With it, canonical views, which capture key visual appearances of landmark with limited redundancy, are efficiently discovered with an iterative mining strategy. Second, multimodal sparse coding is applied …
Can Instagram Posts Help Characterize Urban Micro-Events?,
2016
Singapore Management University
Can Instagram Posts Help Characterize Urban Micro-Events?, Kasthuri Jayarajah, Archan Misra
Research Collection School Of Computing and Information Systems
Social media content, from platforms such as Twitter and Foursquare, has enabled an exciting new field of social sensing, where participatory content generated by users has been used to identify unexpected emerging or trending events. In contrast to such text-based channels, we focus on image-sharing social applications (specifically Instagram), and investigate how such urban social sensing can leverage upon the additional multi-modal, multimedia content. Given the significantly higher fraction of geotagged content on Instagram, we aim to use such channels to go beyond identification of long-lived events (e.g., a marathon) to achieve finer-grained characterization of multiple micro-events (e.g., a person …
Self-Regulated Incremental Clustering With Focused Preferences,
2016
Singapore Management University
Self-Regulated Incremental Clustering With Focused Preferences, Di Wang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Due to their online learning nature, incremental clustering techniques can handle a continuous stream of data. In particular, various incremental clustering techniques based on Adaptive Resonance Theory (ART) have been shown to have low computational complexity in adaptive learning and are less sensitive to noisy information. However, parameter regularization in existing ART clustering techniques is applied either on different features or on different clusters exclusively. In this paper, we introduce Interest-Focused Clustering based on Adaptive Resonance Theory (IFC-ART), which self-regulates the vigilance parameter associated with each feature and each cluster. As such, we can incorporate the domain knowledge of the …
The Effects Of Multiple Query Evidences On Social Image Retrieval,
2016
Singapore Management University
The Effects Of Multiple Query Evidences On Social Image Retrieval, Zhiyong Cheng, Jialie Shen, Haiyan Miao
Research Collection School Of Computing and Information Systems
System performance assessment and comparison are fundamental for large-scale image search engine development. This article documents a set of comprehensive empirical studies to explore the effects of multiple query evidences on large-scale social image search. The search performance based on the social tags, different kinds of visual features and their combinations are systematically studied and analyzed. To quantify the visual query complexity, a novel quantitative metric is proposed and applied to assess the influences of different visual queries based on their complexity levels. Besides, we also study the effects of automatic text query expansion with social tags using a pseudo …
Two Roads, One Destination: A Journey Of Discovery,
2016
Bond University
Two Roads, One Destination: A Journey Of Discovery, Karen Joc, Peta J. Hopkins, Jessie Donaghey, Wendy Abbott
Karen Joc
The adoption of resource discovery platforms has been a growing trend in libraries. However, few libraries have reported on the transition from one discovery layer to another, and only a few institutions have discussed two discovery layers available in the same institution at the same time. Bond University Library recently implemented Alma as its library management system, and with this change a new discovery platform, Primo, was implemented to supersede the existing Summon platform. This paper presents the results of a usability study undertaken at Bond University Library in the move from one discovery layer to another.
Blind And Visually Impaired Users Adaptation To Web Environments: A Qualitative Study,
2016
University of South Florida
Blind And Visually Impaired Users Adaptation To Web Environments: A Qualitative Study, Raneem Saqr
USF Tampa Graduate Theses and Dissertations
Although much research exists on human behavior in online environments, research on users with disabilities is still rare. To draw more attention to this population, this dissertation explored browsing patterns and adaptive behaviors of people with visual disability across different online environments common in daily activities: social network, e-commerce, online information, and search engines’ websites. The main objective of this study is to propose a conceptual framework of how blind and visually impaired users browse and adapt to different web environments. We achieve this objective using a qualitative approach through three studies. In the first study, the researchers collect data …
Exploring The Human Body Space: A Geographical Information System Based Anatomical Atlas,
2016
The University of Maine
Exploring The Human Body Space: A Geographical Information System Based Anatomical Atlas, Antonio Barbeito, Marco Painho, Pedro Cabral, João Goyri O'Neill
Journal of Spatial Information Science
Anatomical atlases allow mapping the anatomical structures of the human body. Early versions of these systems consisted of analogical representations with informative text and labeled images of the human body. With computer systems, digital versions emerged and the third and fourth dimensions were introduced. Consequently, these systems increased their efficiency, allowing more realistic visualizations with improved interactivity and functionality. The 4D atlases allow modeling changes over time on the structures represented. The anatomical atlases based on geographic information system (GIS) environments allow the creation of platforms with a high degree of interactivity and new tools to explore and analyze the …
A Context-Sensitive Conceptual Framework For Activity Modeling,
2016
The University of Maine
A Context-Sensitive Conceptual Framework For Activity Modeling, Rahul Deb Das, Stephan Winter
Journal of Spatial Information Science
Human motion trajectories, however captured, provide a rich spatiotemporal data source for human activity recognition, and the rich literature in motion trajectory analysis provides the tools to bridge the gap between this data and its semantic interpretation. But activity is an ambiguous term across research communities. For example, in urban transport research activities are generally characterized around certain locations assuming the opportunities and resources are present in that location, and traveling happens between these locations for activity participation, i.e., travel is not an activity, rather a mean to overcome spatial constraints. In contrast, in human-computer interaction (HCI) research and in …
Μ-Shapes: Delineating Urban Neighborhoods Using Volunteered Geographic Information,
2016
The University of Maine
Μ-Shapes: Delineating Urban Neighborhoods Using Volunteered Geographic Information, Matt Aadland, Christopher Farah, Kevin Magee
Journal of Spatial Information Science
Urban neighborhoods are a unique form of geography in that their boundaries rely on a social definition rather than a well-defined physical or administrative boundary. Currently, geographic gazetteers capture little more than then the centroid of a neighborhood, limiting potential applications of the data. In this paper, we present µ-shapes, an algorithm that employs fuzzy-set theory to model neighborhood boundaries suitable for populating gazetteers using volunteered geographic information (VGI). The algorithm is evaluated using a reference dataset and VGI from the Map Kibera Project. A confusion matrix comparison between the reference dataset and µ-shape's output demonstrated high sensitivity and accuracy. …
Creating The 2011 Area Classification For Output Areas (2011 Oac),
2016
The University of Maine
Creating The 2011 Area Classification For Output Areas (2011 Oac), Christopher G. Gale, Alexander D. Singleton, Andrew G. Bates, Paul A. Longley
Journal of Spatial Information Science
This paper presents the methodology that has been used to create the 2011 Area Classification for Output Areas (2011 OAC). This extends a lineage of widely used public domain census-only geodemographic classifications in the UK. It provides an update to the successful 2001 OAC methodology, and summarizes the social and physical structure of neighborhoods using data from the 2011 UK Census. The results of a user engagement exercise that underpinned the creation of an updated methodology for the 2011 OAC are also presented. The 2011 OAC comprises 8 Supergroups, 26 Groups, and 76 Subgroups. An example of the results of …
Two Roads, One Destination: A Journey Of Discovery,
2016
Bond University
Two Roads, One Destination: A Journey Of Discovery, Karen Joc, Peta J. Hopkins, Jessie Donaghey, Wendy Abbott
Wendy Abbott
The adoption of resource discovery platforms has been a growing trend in libraries. However, few libraries have reported on the transition from one discovery layer to another, and only a few institutions have discussed two discovery layers available in the same institution at the same time. Bond University Library recently implemented Alma as its library management system, and with this change a new discovery platform, Primo, was implemented to supersede the existing Summon platform. This paper presents the results of a usability study undertaken at Bond University Library in the move from one discovery layer to another.
Two Roads, One Destination: A Journey Of Discovery,
2016
Bond University
Two Roads, One Destination: A Journey Of Discovery, Karen Joc, Peta J. Hopkins, Jessie Donaghey, Wendy Abbott
Wendy Abbott
The adoption of resource discovery platforms has been a growing trend in libraries. However, few libraries have reported on the transition from one discovery layer to another, and only a few institutions have discussed two discovery layers available in the same institution at the same time. Bond University Library recently implemented Alma as its library management system, and with this change a new discovery platform, Primo, was implemented to supersede the existing Summon platform. This paper presents the results of a usability study undertaken at Bond University Library in the move from one discovery layer to another.
